How Much Could American Express Be Affected By Bitcoin Adoption?

by Trefis Team
American Express Company
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The growing popularity of Bitcoins and other cryptocurrencies over recent months has made the widespread adoption of blockchain technology for settling financial transactions a very real possibility. Given these circumstances, it makes sense to understand how the largest payment companies in the world would be affected if companies that offer blockchain-related settlement services eat into their transaction volumes.

We have created a series of interactive models which detail how a 5% reduction in total transaction volume for the three largest payment processing companies in the world – Visa (V), Mastercard (MA) and American Express (AXP) – affects their market price. This article focuses on the interactive model for American Express. You can modify assumptions such as earnings multiples, total transaction volumes, fees as % of transaction volume, effective tax rate and others to see how sensitive American Express’s shares are to its transaction volume.

We maintain a $88 price estimate for American Express’s shares, which is about 10% below the current market price.

As detailed in the chart above, a decrease in American Express’s transaction volume by 5% could reduce its 2018 EPS by $0.16. Using Amex’s current forward P/E ratio of 14.4, this would represent a potential ~$2.35 decline in the bank’s share price – or a downside of nearly 2.5%. This is justified, given the fact that transaction-related revenues constitute over 50% of Amex’s total revenues.

That said, American Express has been one of the early adopters of the blockchain technology among financial institutions – becoming the first card lender to integrate its services with a bitcoin wallet. If American Express continues its push in the cryptocurrency space over coming years, it could more than make up for this lost revenue by taking a more direct role in the industry in the long run.

Think our estimates are off? Create your own estimates by changing the inputs in our interactive model.

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